/stock-historical-index

name: stock-historical-index
description: Retrieve full historical end-of-day price data for market indices using Octagon MCP. Use when analyzing index performance over time, tracking market trends, calculating returns, and understanding market context for individual stock analysis.

Stock Historical Index

Retrieve full historical end-of-day price data for market indices using the Octagon MCP server.

Prerequisites

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See [references/mcp-setup.md](references/mcp-setup.md) for installation instructions.

Workflow

1. Identify Parameters

Determine your query parameters:

• **Index Symbol**: ^GSPC (S&P 500), ^DJI (Dow), ^IXIC (NASDAQ), etc.
• **Start Date**: Beginning of date range
• **End Date**: End of date range

2. Execute Query via Octagon MCP

Use the `octagon-agent` tool with a natural language prompt:

Retrieve full historical end-of-day price data for the <INDEX> index from <START_DATE> to <END_DATE>.

**MCP Call Format:**

{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve full historical end-of-day price data for the ^GSPC index from 2025-01-01 to 2025-04-30."
  }
}

3. Expected Output

The agent returns comprehensive daily index data:

| Date | Open | High | Low | Close | Volume | Change | Change % | VWAP | |------|------|------|-----|-------|--------|--------|----------|------| | 2025-04-30 | 5,499.44 | 5,581.84 | 5,433.24 | 5,569.07 | 5.45B | +69.63 | +1.27% | 5,520.90 | | 2025-04-29 | 5,508.87 | 5,571.95 | 5,505.70 | 5,560.82 | 4.75B | +51.95 | +0.94% | 5,536.84 | | ... | ... | ... | ... | ... | ... | ... | ... | ... |

**Key Statistics**:

• Highest single-day volume: 9.49B on 2025-04-09
• Largest daily gain: +9.90% on 2025-04-09
• Largest daily loss: -4.12% on 2025-04-04
• Trading days covered: 79

**Data Sources**: octagon-stock-data-agent

4. Interpret Results

See [references/interpreting-results.md](references/interpreting-results.md) for guidance on:

• Analyzing index price trends
• Calculating period returns
• Understanding volume patterns
• Identifying significant market moves

Example Queries

**S&P 500 History:**

Retrieve full historical end-of-day price data for the ^GSPC index from 2025-01-01 to 2025-04-30.

**NASDAQ Composite:**

Get historical data for ^IXIC from 2024-01-01 to 2024-12-31.

**Dow Jones:**

Show ^DJI historical prices for Q1 2025.

**Russell 2000:**

Retrieve historical data for ^RUT from 2024-06-01 to 2025-06-01.

**Multiple Indices:**

Compare ^GSPC and ^IXIC performance from 2025-01-01 to 2025-03-31.

Common Index Symbols

US Major Indices

| Symbol | Index | Description | |--------|-------|-------------| | ^GSPC | S&P 500 | 500 large-cap US stocks | | ^DJI | Dow Jones | 30 blue-chip stocks | | ^IXIC | NASDAQ Composite | All NASDAQ stocks | | ^NDX | NASDAQ 100 | 100 largest NASDAQ | | ^RUT | Russell 2000 | 2000 small-cap stocks |

Sector Indices

| Symbol | Index | Description | |--------|-------|-------------| | ^XLK | Technology | Tech sector | | ^XLF | Financials | Financial sector | | ^XLV | Healthcare | Healthcare sector | | ^XLE | Energy | Energy sector | | ^XLI | Industrials | Industrial sector |

Volatility Indices

| Symbol | Index | Description | |--------|-------|-------------| | ^VIX | VIX | Market volatility | | ^VXN | VXN | NASDAQ volatility |

Understanding Index Data

Price Components

| Field | Description | |-------|-------------| | Open | First trade price of day | | High | Highest price of day | | Low | Lowest price of day | | Close | Last trade price of day | | Volume | Total shares traded | | Change | Point change from prior close | | Change % | Percentage change | | VWAP | Volume-weighted average price |

Daily Range Analysis

| Metric | Calculation | |--------|-------------| | Daily Range | High - Low | | Range % | (High - Low) / Open | | Position in Range | (Close - Low) / (High - Low) |

Return Calculations

Period Returns

| Period | Formula | |--------|---------| | Daily | (Close - Prior Close) / Prior Close | | Weekly | (Friday Close - Monday Open) / Monday Open | | Monthly | (Month End - Month Start) / Month Start | | YTD | (Current - Year Start) / Year Start |

Example

From the data:

• Start (Jan 2): 5,868.56
• End (Apr 30): 5,569.07
• Return: (5,569.07 - 5,868.56) / 5,868.56 = -5.10%

Cumulative Returns

Cumulative = (1 + r1) × (1 + r2) × ... × (1 + rn) - 1

Volume Analysis

Volume Patterns

| Pattern | Interpretation | |---------|----------------| | High volume + up | Strong buying | | High volume + down | Strong selling | | Low volume + up | Weak rally | | Low volume + down | Lack of sellers |

Volume Metrics

| Metric | Purpose | |--------|---------| | Average daily volume | Baseline | | Volume spike | Unusual activity | | Volume trend | Participation changes |

Example

From the data:

• Highest volume: 9.49B on 2025-04-09
• This coincided with +9.90% gain (major rally)

Trend Analysis

Trend Identification

| Pattern | Characteristics | |---------|-----------------| | Uptrend | Higher highs, higher lows | | Downtrend | Lower highs, lower lows | | Consolidation | Range-bound | | Reversal | Trend change |

Moving Averages

| MA | Use | |----|-----| | 50-day | Short-term trend | | 200-day | Long-term trend | | Golden Cross | 50 > 200 (bullish) | | Death Cross | 50 < 200 (bearish) |

Volatility Analysis

Measuring Volatility

| Metric | Calculation | |--------|-------------| | Daily Range % | (High - Low) / Close | | Daily Change | Absolute daily change | | Std Deviation | Dispersion of returns |

Volatility Context

| Daily Change % | Market Condition | |----------------|------------------| | <0.5% | Low volatility | | 0.5-1% | Normal | | 1-2% | Elevated | | >2% | High volatility | | >4% | Extreme |